The Adaptive Recommendation Mechanism for Distributed Group in Mobile Environments

Tourism navigation systems have become an important research area because they help people strengthen their focus on the quality of the tourism. This paper proposes an adaptive recommendation mechanism that rests on a congestion-aware scheduling method for multigroup travelers on multidestination travels. This recommendation scheme uses the pheromone mechanism of an ant algorithm for group system distribution. In order to reduce congestion in the “visiting multiple destinations” problem that might beset the multiple groups, we present a tour group that could take adaptive recommendations from a system that would yield a high quality tour experience, wherein the group would visit a secondary destination first and then visit the primary destination. Simulation results reveal the strengths of the proposed “adaptive recommendation mechanism” model in terms of decreasing average waiting time, congestion, and the ratio of congestion avoiding to number of groups.